Introduction

Introduction to Computing Systems: From bits & gates to C & beyond
$87.50
I had programmed in a number of languages including C before, but I was a bit intimidated by assembler. I was also curious about how microchips work, and why they seem to be all about transistors. There's a lot of material on the web on this subject, but none of it seems detailed and organized enough to really teach you anything. After reading this book, it all makes sense.

There are some great sections including simple, excellent explanations of 2s-complement numbers and finite state machines. I'd recommend this book to anyone who already programs in C, and has played a bit with pointers - I'm not sure I would have liked to encounter them for the first time in this text.

The book is not perfect. Its pace is very slow, and authors often threw in "real-world" analogies which I didn't find helpful. Some sections are a bit repetitive. There were a few concepts thrown in without careful introduction, for example call-by-value vs. call-by-reference. Again, that's not a serious problem if you have even passing familiarity with C.

Overall, a gradual, relaxed, well-structured introduction to a fascinating subject. Good preparation for further study.

Living Rock: Introduction to Earth's Geology
$24.95
I bought this video to show to my 8th grade science class. It is very informative and covers a vast array of topics that relate to our curriculum, but the delivery is very dry. The narrator speaks almost in monotone. It is full of great information that will benefit the students if they could stay focused. I was told by many students "Miss, this is soooo boring!".

CAIA Level I: An Introduction to Core Topics in Alternative Investments (Wiley Finance)
$195.00
The official study text for the Level I Chartered Alternative Investment Analyst (CAIA) exam The Chartered Alternative Investment Analyst (CAIA) designation is the financial industry's first and only globally recognized program that prepares professionals to deal with the ever-growing field of alternative investments. The CAIA Level I: An Introduction to Core Topics in Alternative Investments contains all material on alternative investments that a potential Level I candidate would need to know as they prepare for the exam. The information found here will help you build a solid foundation in both traditional and alternative investment markets-for example, the range of statistics that are used to define investment performance as well as the many types of hedge fund strategies. It will also inform CAIA candidates on how to identify and describe aspects of financial markets, develop reasoning skills, and in some cases, make computations necessary to solve business problems. Contains "need to know" material for Level I candidates and for alternative investment specialists Addresses all of the unique attributes associated with the alternative investments space Organized with a study guide outline and learning objectives with key terms, available for free at www.caia.org/program/studyguides Focuses on alternative investments and quantitative techniques used by investment professionals This book is a must-have resource for anyone contemplating taking the CAIA Level I exam.

Introduction to Algorithms, Third Edition
$87.00
An algorithm is nothing more than a set of computational steps that transform a specific input into a desired output. From that definition, there are plenty of books on the market that are "cookbooks" of algorithms and will enable you to do just that - transform specific inputs into outputs, complete with source code, and with no real depth of understanding of your own required. However, to be a computer scientist versus a programmer, you need to know what makes an efficient algorithm, why is a particular algorithm efficient, what kinds of common data structures are involved in various computing problems, how to traverse those data structures efficiently, and a notation for analyzing various algorithms. This book will help you learn all of that. The study of the theory of algorithms is not to be undertaken lightly, and I don't recommend you attempt to self-study such a complex subject with such strong mathematical underpinnings. In fact, this book is really aimed at graduate computer science students and is often on the reading list of Ph.D. qualifying examinations in that field.

For students of graph theory, you might find your knowledge solidly supplemented by the material in chapters 22 through 26 on graph algorithms. The last section of the book, "Selected Topics", goes over various specific algorithms from many fields using the knowledge of algorithm design and analysis you have learned up to this point in the book. Throughout, the text is very clear, and there are plenty of instructive diagrams and pseudocode.

One of the most interesting parts of the book is the chapter on NP-completeness. This is the study of problems for which no efficient algorithm has ever been found. These problems are interesting for two reasons. The first being that even though an efficient algorithm has never been found, there is no proof that one cannot exist. Second, if an efficient algorithm exists for one of them, then an efficient algorithm exists for all. Thus, if you are ever called upon to write an efficient algorithm for an NP-complete problem, you will be involved in a long fruitless search if you do not recognize the problem as NP-complete. If you can show the problem is NP-complete, you can go about producing an algorithm that gives a good solution, but not the best possible solution. This kind of knowledge is what separates a computer scientist from a mere programmer, and is one of many reasons to study this book's contents. I highly recommend this book to anyone who truly wants to be called a computer scientist.

To get the most from this book you should already be familiar with discrete mathematics and combinatorics, as this book makes heavy use of these subjects. Because this book contains no solutions to any of the exercises, might I suggest "Problems on Algorithms" by Ian Parberry as a companion to this book. It has a little bit of tutorial and a lot of exercises, many unsolved, but some with hints and others with solutions. Also, for more basic material, you might look at "Schaum's Outline of Discrete Mathematics". It's very inexpensive and can almost stand alone as a tutorial on the mathematics you need to know to succeed at understanding this book. The table of contents is not shown for this third edition of the book, so I supply that information next:

Table of Contents
Preface
I Foundations
1 The Role of Algorithms in Computing
2 Getting Started
3 Growth of Functions
4 Recurrences
5 Probabilistic Analysis and Randomized Algorithms
II Sorting and Order Statistics
6 Heapsort
7 Quicksort
8 Sorting in Linear Time
9 Medians and Order Statistics
III Data Structures
10 Elementary Data Structures
11 Hash Table
12 Binary Search Trees
13 Red-Black Trees
14 Augmenting Data Structures
IV Advanced Design and Analysis Techniques
15 Dynamic Programming
16 Greedy Algorithms
17 Amortized Analysis
V Advanced Data Structures
18 B-Trees
19 Binomial Heaps
20 Fibonacci Heaps
21 Data Structures for Disjoint Sets
VI Graph Algorithms
22 Elementary Graph Algorithms
23 Minimum Spanning Trees
24 Single-Source Shortest Paths
25 All-Pairs Shortest Paths
26 Maximum Flow
VII Selected Topics
27 Sorting Networks
28 Matrix Operations
29 Linear Programming
30 Polynomials and the FFT
31 Number-Theoretic Algorithms
32 String Matching
33 Computational Geometry
34 NP Completeness
35 Approximation Algorithms